Browse Topic: Braking systems

Items (5,458)
The Electrohydraulic Brake Valve (EBV) is a vital component in full-power brake systems for heavy-duty and off-highway vehicles, providing precise hydraulic pressure modulation through electrical control. Traditionally, EBV housings are manufactured using bar-machined components, which offer durability but contribute significantly to the overall weight and cost of the assembly. In response to increasing demands for lightweight and cost-effective solutions, this study presents a targeted design optimization of the EBV housing. The redesigned housing adopts a casting-based geometry, integrates sensor ports for pressure monitoring, and includes a nameplate mounting provision for customer identification. Material substitution and structural simplification were employed to enhance manufacturability and performance. Finite Element Analysis (FEA) was used to validate the mechanical integrity of the new design under operational conditions. The optimized EBV assembly achieved a weight reduction
R, Thangarajan
Conventional tractor transmission systems feature separate Brake and Bull Cage housings, with brakes often being proprietary components and Bull Cage designed by the Original Equipment manufacturer (OE). To optimize design and performance, an innovative integrated system was developed, combining an in-house braking system with a unitized Bull Cage assembly. This robust design reduces part count, eliminates proprietary dependency (except for friction liners), and enhances performance. Virtual simulations performed under RWUP conditions demonstrated enhanced strength and stiffness in the integrated design. In this Integrated Brake & Bull Cage assembly (IBCA), the braking layout was reconfigured from a 4+1 friction design to a 3+2 configuration which improved balancing, enhancing customer braking experience and increasing contact area by 11%. This adjustment extends friction liner life and boosts mechanical advantage by 7.9%, significantly improving tractor stability and performance
Dumpa, Mahendra ReddyDhanale, SwapnilPerumal, SolairajGomes, MaxsonRedkar, DineshSavant, KedarnathV, Saravanan
The Automobile Life Extender (ALE) comprises an on-board function, a machine learning model operating via cloud computing and a smartphone app. The on-board function receives signals such as engine RPM, throttle position, brake pedal position, and hydraulic pressure from the vehicle's ECUs. Based on this data, the on-board ALE module calculates the engine load, brake circuit load, etc., and sends it to the predictive maintenance model via the on-board IoT system. The predictive maintenance model contains recorded data about the type of engine, brake system, and their performance curves acquired from tests conducted by its OEM. Machine learning models holds a crucial role in dynamically analyzing vehicle data, identifying drive patterns, and predicting the need for maintenance of a part or system. A hybrid approach of training models based on supervised and unsupervised learning is incorporated, creating an active learning strategy to maximize the use of available data. Amazon SageMaker
Sundaram, RameshselvakumarKumar, LokeshSaint Peter Thomas, EdwinSureshkumar, SrihariMuthukumaran, ChockalingamMenon, Abhijith
This study focuses on the vibration analysis of hybrid composite laminated plates fabricated from E-glass Fiber and areca Fiber reinforced with epoxy resin. The hybrid laminates were prepared using the Vacuum Assisted Resin Transfer Moulding (VARTM) process with different stacking sequences and Fiber ratios, where brake lining powder was also incorporated as a filler in selected configurations to enhance mechanical and damping properties. The fabricated plates (280 × 280 mm) were subjected to experimental modal analysis using an impact hammer and accelerometer setup, with data acquisition carried out through DEWESoft software. Natural frequencies and damping ratios were determined under three boundary conditions (C- C-C-C, C-F-C-F, and C-F-F-F). The results revealed that Plate 1, with E-glass outer layers, areca reinforcement, and filler addition, exhibited the best vibration performance, achieving a maximum natural frequency of 332.8 Hz under C-C-C-C condition, while Plate 2 showed a
D R, RajkumarO, Vivin LeninR, SaktheevelR G, Ajay KrishnaNg, Bhavan
The recently increasing global concern about sustainability and greenhouse gas emission reduction has boosted the diffusion of electric vehicles. Research on this topic mainly focuses on either re-designing or adapting most conventional vehicle subsystems, especially the propulsion motor and the braking components. In this context, the present work aims to model, analyze, and compare three-braking system layouts design alternatives focusing on their contribution to vehicle performance and efficiency: a commercial vacuum-boosted hydraulic braking system, a commercial integrated electrohydraulic braking system, and a concept distributed electrohydraulic brake system. Braking systems performance are evaluated by simulating key maneuvers adopting a full model of a battery electric vehicle (BEV), which includes all relevant components like tires, and powertrain dynamics, which is validated against real-world data. Implementation and integration of the first two systems are discussed
Savi, LorenzoGarosio, DamianoFloros, DimosthenisVignati, MicheleTravagliati, AlessandroBraghin, Francesco
Predictive maintenance is critical to improving reliability, safety and operational efficiency of connected vehicles. However, classic supervised learning methods for fault prediction rely heavily on large-scale labeled data of failures, which are difficult to obtain and maintain a manually built dataset of failure events in real automotives settings. In this paper, we present a novel self-supervised anomaly detection model that makes predictions on the faults without the need for labeled failures by using only the operational data when the systems or robots are healthy. The method relies on self-supervised pretext tasks, like masked signal reconstruction and future telemetry prediction, to extract nominal multi-sensor dynamics (i.e., temperature, pressure, current, vibration) while jointly minimizing the deviation between encoded/decoded signals and normal patterns in the latent space. A unsupervised anomaly detection model is then used to detect when the learned patterns are violated
Kumar, PankajDeole, KaushikHivarkar, Umesh
Engine braking is a deceleration technique that leverages the internal friction and pumping losses within the engine. By closing the throttle and potentially selecting a lower gear, the engine creates a retarding force that slows the vehicle. This practice contributes to better fuel economy, decreased brake system load, and improved vehicle handling in specific driving scenarios, such as steep declines or slippery road surfaces. To alleviate stress on their primary braking systems and prevent overheating, heavy vehicles frequently incorporate engine-based braking. While older trucks relied on simple exhaust brakes with a butterfly valve to restrict exhaust flow, these had limited impact. Hence contemporary heavy vehicles almost exclusively use more advanced engine braking technologies. Traditionally, our heavy-duty vehicles use Exhaust brake system to elevate the braking performance on hilly terrains. Hence an improved sample of Engine brake was developed for enhanced braking
M, Vipin PrakashRajappan, Dinesh KumarR, SureshN, Gopi Kannan
Recent regulations limiting brake dust emissions have presented many challenges to the brake engineering community. The objective of this paper is to provide a low cost, mass production solution utilizing well known existing technologies to meet brake emissions requirements. The proposed process is to alloy the Gray Cast Iron with Niobium and subsequently Ferritic Nitrocarburize (FNC) the disc. The Niobium addition will improve the wear resistance of the FNC case, reducing wear debris. The test methodology included: 1. Manufacture of disc samples alloyed with Niobium, 2. Finish machining and ferritic nitrocarburizing and 3. Evaluation of airborne wear debris utilizing a pin-on-disc tribometer equipped with emission collection capability. The airborne emission and wear surfaces were further analyzed by Scanning Electron Microscopy, Energy Dispersive techniques (SEM-EDS), X-Ray Diffraction and Optical Microscopy. The cast iron test matrix included four groups; Unalloyed eutectic 4.3
Barile, BernardoHolly, Mike
Agricultural operations in hilly, uneven & slopy terrains demands high levels of operator focus, effort and skill. However, todays farming ecosystem across the globe is affected by 2 major scenarios: the aging workforce in the agricultural sector and the ever-growing problem of distraction due to mobile device and social media use. These issues compromise safety during operations such as start stop maneuvers, parking on slopes, and maneuvering in confined & narrow areas. Stringent emission norms are also being mandated across developed and developing countries as a measure to reduce Global Greenhouse house gas emissions. These measures are indeed necessary for sustainability but has increased overall tractor purchase and operating costs without improving safety & operator comfort. There has been a trend seen around the world in terms of poor sales post Emission implementation. Registration of Older tractors without these stringent emission norms were also witnessed in Developed
M, RojerT, GanesanP, VelusamyNatarajan, SaravananV, Mathankumartripathi, ShankarNarni, KiranHaldorai, RajanDevakumar, Kiran
The objective of this paper is to evaluate the thermal performance of the brake discs in the design stage of its life cycle by developing a methodology to replicate dynamometer testing using multi-disciplinary Finite Element Analysis (FEA) methods. A simulation workflow was formulated in which Computational Fluid Dynamics (CFD) was used to create temperature and velocity dependent Heat Transfer Coefficients (HTC) which were in turn used in Computer Aided Engineering (CAE) to do a thermo-mechanical analysis. With this workflow various designs of the brake discs were analyzed. A sensitivity study was done to determine critical design features that affected its thermal performance. A final design was fixed that met both the weight and thermal performance targets. This design was evaluated in dynamometer testing, and 93% correlation was achieved. Thus, the developed simulation workflow ensured that a first-time right brake disc can be finalized in the design stage, which will meet the
Balaji, PraveenK, KarthikeyanS, KesavprasadS Kangde, SuhasReddy, Jagadeeswara
Accurate range estimation in battery electric vehicles (BEVs) is essential for optimizing performance, energy efficiency, and customer expectations. This study investigates the discrepancies between physical test data and simulation predictions for the BEV model. A detailed range delta analysis identifies key contributors to the observed deviations, including regenerative braking inefficiencies, increased propulsion demand, auxiliary loads, and estimated drivetrain losses within the Electric Drive Module (EDM) during traction and regen. Results indicate that the test vehicle exhibits lower regenerative braking efficiency, higher traction forces and lower regen energy than predicted by simulations, primarily due to EDM inefficiencies and friction brake usage during regeneration. The study underscores the importance of refining simulation methodologies by integrating real-world, test based EDM loss maps to improve accuracy and better align predictive models with actual vehicle
Mahajan, PrasadKesarkar, SidheshAli, Shoaib
Overloading in vehicles, particularly trucks and city buses, poses a critical challenge in India, contributing to increased traffic accidents, economic losses, and infrastructural damage. This issue stems from excessive loads that compromise vehicle stability, reduce braking efficiency, accelerate tire wear, and heighten the risk of catastrophic failures. To address this, we propose an intelligent overloading control and warning system that integrates load-sensing technology with real-time corrective measures. The system employs precision load sensors (e.g., air below deflection monitoring via pressure sensors) to measure vehicle weight dynamically. When the load exceeds predefined thresholds, the system triggers a multi-stage response: 1 Visual/Audio Warning – Alerts the driver to take corrective action. 2 Braking Intervention – If ignored, the braking applied, immobilizing the vehicle until the load is reduced. Experimental validation involved ten iterative tests to map deflection-to
Raj, AmriteshPujari, SachinLondhe, MaheshShirke, SumeetShinde, Akshay
Electric Vehicles and Plug-in Hybrids alleviate the energy crisis but pose a unique challenge for vehicle dynamics. Though significant developments in motor control strategy and energy density management are evolving, we face significant challenges in torque management, with several ADAS features being an integral part of the EVs/xHEVs. It demands high-fidelity physical and control model exchanges between electric chassis, ride-handling, tire modelling, steering assist, powertrain, and validation using a 0D–1D platform. This paper explicates a unified strategy for improving overall vehicle performance by intelligently distributing and coordinating drive torque to enhance traction, stability, and drivability across diverse operating conditions through co-simulation. The co-simulation platform includes physical models in AMESIM, and control strategies integrated in MATLAB/Simulink. The platform features comprehensive representations of digital vehicles that require detailed modelling of
Eruva, PatrickxavierSarapalli Ramachandran, RaghuveeranChougule, SourabhNatanamani-Pillai, Siva SubramanianScheider, ClementLeclerc, CedricNatarajasundaram, Balasubramanian
Nowadays, vehicle enthusiasts often vary the driving patterns, from high-speed driving to off-roading. This leads to a continuous increase in demand for four-wheel drive (4WD) vehicles. A 4WD vehicle have better traction control with enhanced stability. The performance and reliability of 4WD vehicles at high speeds are significantly influenced by driveline stiffness and natural frequency, which are largely affected by the propeller shaft and transfer case. This study focuses on the design optimization of the transfer case and the propeller shafts to enhance the vehicle performance at high speeds. The analysis begins with a comprehensive study of factors affecting the power transfer path, transfer case stiffness, and critical frequency, including material properties, propeller shaft geometry, and different boundary conditions. Advanced computational methods are employed to model the dynamic behavior of the powertrain, identifying the natural frequency of the transfer case and propeller
Kumar, SarveshYadav, SahdevS, ManickarajaSanjay, LKanagaraj, PothirajJain, Saurabh KumarDeole, Subodh M
In agricultural tractors, braking actuation is usually done through control linkages consisting of a series of connected four-bar linkages with multiple pivots from the pedal to the brake pads. The quality of force transmission is critical as it directly affects the braking performance of the tractor. Forces measured at the end of the control linkage or brake pull rod often show deviation from theoretical values based on mechanical advantage calculations. This is due to various factors such as linkage transmission angle, elasticity, and friction losses in joints. A standardized simulation method needs to be developed and validated to predict the losses in the control linkage system. In this paper, the author proposes a simulation approach using multi-body dynamics, which includes contribution factors such as transmission angle, linkage elasticity, and friction in joints. MBS models for brake linkage systems for three different tractors were developed with flex bodies using ADAMS/View
Subbaiyan, Prasanna BalajiNizampatnam, BalaramakrishnaRedkar, DineshArun, GK, VinothR, SengottuPaulraj, Lemuel
Special vehicles such as off-road vehicles and planetary rovers frequently operate on complex, unpaved road surfaces with varying mechanical parameters. Inaccurate estimation of these parameters can cause subsidence or rollover. Existing methods either lack proactive perception or high precision. This article proposes a fusion framework integrating a visual classifier and a dynamics observer for stable, accurate estimation of road surface parameters. The visual classifier uses an adaptive segmentation system for unpaved roads, leveraging a large-scale vision model and a lightweight network to classify upcoming road surfaces. The dynamics observer employs an online wheel-–ground interaction model using stress approximation, integrating strong tracking theory into an unscented Kalman filter for real-time parameter estimation. The fusion framework performs integration of the classifier and observer outputs at data, feature, and decision levels. An adaptive fading factor and recursive
Zhang, ChenhaoXia, GuangZhang, YangZhou, DayangShi, Qin
In recent years, the automotive industry has been looking into alternatives for conventional vehicles to promote a sustainable transportation future having a lesser carbon footprint. Electric Vehicles (EV) are a promising choice as they produce zero tail pipe emissions. However, even with the demand for EVs increasing, the charging infrastructure is still a concern, which leads to range anxiety. This necessitates the judicious use of battery charge and reduce the energy wastage occurring at any point. In EVs, regenerative braking is an additional option which helps in recuperating the battery energy during vehicle deceleration. The amount of energy recuperated mainly depends on the current State of Charge (SoC) of the battery and the battery temperature. Typically, the amount of recuperable energy reduces as the current SoC moves closer to 100%. Once this limit is reached, the excess energy available for recuperation is discharged through the brake resistor/pads. This paper proposes a
Barik, MadhusmitaS, SethuramanAruljothi, Sathishkumar
Brake response time in truck air brake systems is crucial for ensuring safety and operational efficiency. This paper details the development of a simulation model aimed at fulfilling all regulatory requirements for brake response time, as well as serving as a tool for stopping distance calculations. The actual pneumatic circuit, including brake valves, relay valves, brake chambers, and plumbing have been replicated. The aim is to use 1D simulations to predict the response time compliance during the pressurizing phase (when brakes are applied) of the brake system. A mathematical model is developed using a commercially available 1D simulation tool. This model employs a lumped parameter approach for the pneumatic components, with governing equations derived from compressible flow theory and empirical valve flow characteristics. The simulation outcomes provide detailed response time and pressure build-up profiles. Validation against 201 vehicle test cases showed 96% of simulations within
Kumbar, PrafulMurugesan, KarthikShannon, Rick
This study presents an integrated vehicle dynamics framework combining a 12-degree-of-freedom full vehicle model with advanced control strategies to enhance both ride comfort and handling stability. Unlike simplified models, it incorporates linear and nonlinear tire characteristics to simulate real-world dynamic behavior with higher accuracy. An active roll control system using rear suspension actuators is developed to mitigate excessive body roll and yaw instability during cornering and maneuvers. A co-simulation environment is established by coupling MATLAB/Simulink-based control algorithms with high-fidelity multibody dynamics modeled in ADAMS Car, enabling precise, real-time interaction between control logic and vehicle response. The model is calibrated and validated against data from an instrumented test vehicle, ensuring practical relevance. Simulation results show significant reductions in roll angle, yaw rate deviation, and lateral acceleration, highlighting the effectiveness
Duraikannu, DineshDumpala, Gangi Reddi
In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing
Kumar, AkhileshV, Yashvati
The Objective is to develop a testing load case which can assess vehicle electric parking brake (EPB) performance and durability at vehicle level in different project development phases. In current scenario the EPB become one of a primary feature available in many passenger vehicles helps customers to apply this secondary braking system to hold the vehicle when parked. So, it is particularly important to evaluate this feature close to RWUP for the vehicle service life and studying the result before vehicle launch. The test method should be capable of capturing failures related to physical concerns, electrical characteristics, actuation time, gradient vehicle hold, effectiveness during vehicle running and durability. The most important challenge in this test method development is it should simulate the actual sequence followed by user in field on vehicle. A completely automated test set up integrating PLC and COBOT with closed loop feedback developed and discussed in this paper. During
Dhanapal, M RVijayakumar, NarayananMahesh, BB, VenkatasubramanianArthanathan, Sankaranarayanan
As the brain and the core of the electric powertrain, the traction inverter is an essential part of electric vehicles (EVs). It controls the power conversion from DC to AC between the electric motor and the high-voltage battery to enable effective propulsion and regenerative braking. Strong and scalable inverter testing solutions are becoming more essential as EV adoption rises, particularly in developing nations like India. In India, traditional testing techniques that use actual batteries and e-motors present several difficulties, such as significant safety hazards, inadequate infrastructure, expensive battery prices, and a shortage of prototype-grade parts. This paper presents a comprehensive approach for traction inverter validation using the AVL Inverter TS™ system incorporating an advanced Power Hardware-in-the-Loop (PHiL) test system based on e-motor emulation technology. It enables safe, efficient, and reliable testing eradicating the need for actual batteries or mechanical
Mehrotra, SoumyaChhabra, Rishabh
A significant contributor to particle mass (PM) emissions originating from road transport are particles emitted from brakes, which in Europe are considered in the upcoming Euro 7 emission legislation. UN-GTR (United Nations Global Technical Regulation) no. 24 describes the methodology for measuring brake particle emissions in a test cell setting with a dynamometer, both in terms of PM and PN (particle number). A regulation-compliant test fulfills various quality criteria for different control parameters, which can often be met by applying different control strategies. In this study, we evaluate the effects of implementing different control strategies for torque applied to the brake by the dynamometer, as well as for sampling flow. Additionally, we discuss the cost-saving potential of increasing the automation degree of testing, as well as modifying existing testbeds to accommodate brake emission testing. The torque control strategies applied in this study did not influence PN or PM
Martikainen, SampsaWeidinger, ChristophHuber, Michael Peter
In automotive safety systems, Time to Collide (TTC) is traditionally used to trigger warnings in auto-emergency braking systems. However, TTC can lead to premature or inaccurate warnings as it is calculated based on the relative speed and distance between the ego and an obstacle. TTC does not consider the vehicle’s braking dynamics, such as brake prefill lag which varies across different vehicles, maximum deceleration, and the effectiveness of braking systems and assumes constant speed which may not always be realistic. We propose Time to Brake (TTB) as a more effective parameter for driver warnings. TTB directly relates to the action a driver needs to take—braking. It provides a clear indication of when braking should begin to avoid a collision, whereas TTC only tells us about the possibility of a collision. To calculate TTB we utilize the brake profile, which incorporates both deceleration and system jerk for improved accuracy. The proposed warning time is the sum of variable brake
Singh, Ashutosh PrakashKumawat, HimanshuGupta, Sara
The main focus of this paper is to create a more efficient regenerative braking control strategy for electric commercial buses operating under Indian road conditions. The strategy uses Artificial Neural Networks (ANNs) to optimize regenerative braking process. Regenerative braking helps to recover energy that would otherwise be lost during braking and convert it back into usable power for the vehicle. The challenge is to design a system that works effectively on the diverse and often challenging road conditions found in India, such as varying gradients, traffic patterns, and road surface types. This study begins by collecting data (which includes vehicle speed, traffic condition, etc.) from real-world driving conditions and aims to train an Artificial Neural Network (ANN) using a large set of driving data which is collected under various conditions to predict the most efficient regenerative braking settings for different driving scenarios. This research brings a new approach to the
Saurabh, SaurabhBhardwaj, RohitPatil, NikhilGadve, DhananjayAmancharla, Naga Chaithanya
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